Aidan Soares Oliveira

Aidan Soares Oliveira joined the Peterson Institute for International Economics as a research analyst in August 2026. His work centers on a research project, supported by the Alfred P. Sloan Foundation and headed by PIIE Senior Fellow Jed Kolko, that examines the production and integrity of government economic statistics.

Prior to joining PIIE, Oliveira spent two years as a research analyst at the Federal Reserve Bank of New York, where he assisted with empirical research on labor markets and contributed to the construction and integration of datasets used for policy and academic research. Some of these latter projects included assembling a dataset of local government investment pools and a project linking financial data on banks (with publicly traded securities) to regulatory banking data. He was also a machine learning graduate summer intern at the Federal Reserve Bank of Philadelphia where he constructed interactive visualizations of various parity measures used to detect bias in the mortgage market (using Home Mortgage Disclosure Act data). These parity measures include representativeness, equalized odds, statistical parity, conditional parity, and statistical-conditional parity.

Oliveira holds a master's degree in economics from Tufts University, where he was a Future Leaders Fellow, a teaching assistant for graduate-level economics courses, and a part-time research assistant working on a project involving US Department of Housing and Urban Development administrative data. His master's thesis explored the relationship between occupational specialization, firm growth, and agglomeration economies. He also holds a master's degree in regional science from Cornell University, where his thesis developed a spatial model of interdependent firm and residential location to explain how agglomeration economies shape polycentric urban form.

He is interested in topics related to local public finance as well as urban and spatial economics, especially in how the organization of economic activity within firms is mediated by forces stemming from the interaction between labor markets, financial markets, and place. His work at PIIE adds a complementary focus on economic measurement: how the statistics used to classify and measure workers, occupations, firms, industries, financial markets, and places are produced; how they depend on one another; and how changes in their construction can influence empirical analysis.